We present a novel technique for processing image similarity search by using an approach that takes inspiration from text retrieval techniques. In our approach images are indexed by using visual terms taken from a visual lexicon obtained clustering regions of images in the dataset. A weighting and matching schema is defined that allow effective image retrieval to be performed by using inverted files, thus requiring reduced storage space and achieving high efficiency.